def testZFlag(self):
"""This test looks at the l flag and determines if the dictionary reads the specified requested letter""" ""
sys.argv = ['-z', 'text.txt']
print('testsys', sys.argv)
result = count.main()
print('testResult: ', result)
check = {
'a': 2,
'b': 2,
'c': 2,
'd': 2,
'e': 0,
'f': 0,
'g': 0,
'h': 0,
'i': 0,
'j': 0,
'k': 0,
'l': 0,
'm': 0,
'n': 0,
'o': 0,
'p': 0,
'q': 0,
'r': 0,
's': 0,
't': 0,
'u': 0,
'v': 0,
'w': 0,
'x': 0,
'y': 0,
'z': 0
}
self.assertDictEqual(result, check)
def testCFlag(self):
"""This test looks at the l flag and determines if the dictionary reads the specified requested letter""" ""
sys.argv = ['-c', 'text.txt']
print('testsys', sys.argv)
result = count.main()
print('testResult: ', result)
check = {'A': 2, 'b': 2, 'C': 1, 'c': 1, 'D': 1, 'd': 1}
self.assertDictEqual(result, check)
def main():
settings.init()
flag = True
count.main(0, 'detector')
print("Starting Face Detection Technique")
for i in trange(0, 10):
time.sleep(0.01)
print(" If Data Already Feeded.(Press Ctrl Z)")
while (flag):
count.main(1, 'face_dataset_creater')
try:
print(
"Press Enter To Skip To Recognition Part or Any Key To Feed New Data :"
)
flag = input()
except:
flag = False
count.main(2, 'trainner')
count.main(3, 'recogniser')
count.main(4, 'detector')
print("Completed")
print(settings.myList)
def count_to_csv():
csvArgs = sys.argv
csvFileArgs = [i for i in csvArgs if '.csv' in i]
csvFileName = ""
for i in csvFileArgs:
csvFileName += i
csvArgs.remove(csvFileName) ###Removes file name from args
d={}
d = count.main()
a_file = open(csvFileName, "w") ###Writing the dictionary to CSV
csvWriter = csv.writer(a_file)
for key, value in d.items():
csvWriter.writerow([key,value])
a_file.close()
print('Your file has been saved as a CSV: ', csvFileName)
async def end_election(ctx, seats):
#print("Almost there")
votelist = {}
party = 1
party_list = list(find_parties(client).keys())
async for msg in ctx.channel.history(limit=100):
message = await ctx.channel.fetch_message(msg.id)
reaction = get(message.reactions, emoji='✅')
if type(reaction) != type(None):
votelist[party_list[len(party_list) - party]] = (reaction.count -
1)
if len(party_list) - party == 0:
break
party += 1
print(votelist)
seatlist = count.main(int(seats), votelist)
await ctx.send(seatlist)
parser.add_argument('--coverage' , required=True,type=str, help="the tab file containing coverage tab files")
parser.add_argument('--ploidy' , type=int,default = 2,help="the ploidy of the organism")
parser.add_argument('--d' , type=float,default=0.1,help="minimum ratio deviation to call chromosomal abberation")
parser.add_argument('--gc' , type=str,required= True, help="the tab file containing gc content")
parser.add_argument('--c_cutoff' , type=int,default=200,help="bins having coverage higher than the cut off value are excluded from the ref calculations")
parser.add_argument('--s_cutoff' , type=int,default=50,help="bins that have less than the s_cutoff value similar bins are discarded from copy nmber esitmation")
parser.add_argument('--refQ' , type=int,default=30,help="Minimum average mapping quality of the bins used for constructing the reference = 30")
parser.add_argument('--Q' , type=int,default=30,help="Minimum average mapping quality of the bins used for copy number estimation default = 30")
args = parser.parse_args()
Data = common.gc_tab(args.gc)
#compute a gc content histogram
Data=common.coverage_tab(args.coverage,Data)
GC_hist=common.gc_hist(Data,args.c_cutoff,args.s_cutoff,args.refQ)
count.main(Data,GC_hist,args)
elif args.filt:
parser = argparse.ArgumentParser("""AMYCNE-filter: filter the coverage tab file, prints it to stdout for later use""")
parser.add_argument('--gc' , type=str,required= True, help="the tab file containing gc content")
parser.add_argument('--coverage' , type=str,required= True,default=None, help="the tab file containing coverage")
parser.add_argument('--c_cutoff' , type=int,default=100,help="bins having coverage higher than the cut off value are excluded from the ref calculations")
parser.add_argument('--s_cutoff' , type=int,default=50,help="bins that have less than the s_cutoff value similar bins are discarded from copy nmber esitmation")
parser.add_argument('--filter' , type=int,default=2000,help="size of the filters, default = 2000")
parser.add_argument('--refQ' , type=int,default=30,help="Minimum average mapping quality of the bins used for constructing the reference = 30")
parser.add_argument('--Q' , type=int,default=10,help="Minimum average mapping quality of the bins used for copy number estimation default = 10")
parser.add_argument('--filt' , action="store_true" ,help="perform CNV calling")
args = parser.parse_args()
Data = common.gc_tab(args.gc)
def test_clz(self): #-c, -l, and -z flags
sys.argv = ['count.py', '-c', '-l', 'Aabcz', '-z', path]
self.assertEqual(c.main(), self.dclz)
def test_cz(self): #-c and -z flags
sys.argv = ['count.py', '-c', '-z', path]
self.assertEqual(c.main(), self.dcz)
def test_cl(self): #-c and -l flags
sys.argv = ['count.py', '-c', '-l', 'Aabc', path]
self.assertEqual(c.main(), self.dcl)
def test_z(self): #-z flag only
sys.argv = ['count.py', '-z', path]
self.assertEqual(c.main(), self.dz)
def test_l(self): #-l flag only
sys.argv = ['count.py', '-l', 'Aabc', path]
self.assertEqual(c.main(), self.dl)
def test_c(self): #-c flag only
sys.argv = ['count.py', '-c', path]
self.assertEqual(c.main(), self.dc)
def test_null(self): #no flags
sys.argv = ['count.py', path]
self.assertEqual(c.main(), self.d)
#!/usr/bin/env python3
## Krista Miller
## Data Science 2, Project 02, Counting Characters -- Reference Implementation
import count as c
import sys
import csv
d = c.main()
args = sys.argv
CSV_name = None
for a in args:
if a.endswith(".csv"):
CSV_name = a
l=list(d.items())
with open(CSV_name, "w", encoding='utf8', newline="") as csvfile:
writer = csv.writer(csvfile)
writer.writerows(l)
def main2():
return count.main()